stata_example

use "S:\SAMF-SOC-Coronaogsolidaritet\Analyse\DST befolkningssurvey\Data\renset\KUFrivillighed2020_4_panel_runder_merged_long_format_temp.dta", clear 

encode resp_id1, gen(respondent)
xtset respondent round

* Kontrolvariable og socio-økonomi

** Køn
bysort respondent (round): generate kvinde = koen[1]==2 

** Alder
bysort respondent (round): generate ung_alder = alder_grp[1]<=2
bysort respondent (round): generate mid_alder = alder_grp[1]>=3 & alder_grp[1]<=5
bysort respondent (round): generate gam_alder = alder_grp[1]>=6

** Risikogruppe
bysort respondent (round): generate risiko = alvorligt[1]>=5 if alvorligt[1]<.

** Helbred
bysort respondent (round): generate daarligthelbred = helbred[1]<=3 if helbred[1]<.

** Uddannelse
bysort respondent (round): generate grundskolde = udgrp[1]==1 if udgrp[1]<.
bysort respondent (round): generate kvu = udgrp[1]==2 if udgrp[1]<.
bysort respondent (round): generate mvu = udgrp[1]==3 if udgrp[1]<.
bysort respondent (round): generate lvu = udgrp[1]==4 if udgrp[1]<.

** Beskæftigelse
bysort respondent (round): generate ibeskaef = beskaef_h[1]==1 if beskaef_h[1]<.
bysort respondent (round): generate udenbeskaef = beskaef_h[1]==2 if beskaef_h[1]<.
bysort respondent (round): generate pensionist = beskaef_h[1]==3 if beskaef_h[1]<.
bysort respondent (round): generate studerende = beskaef_h[1]==4 if beskaef_h[1]<.
bysort respondent (round): generate andet = beskaef_h[1]==5 if beskaef_h[1]<.

bysort respondent (round): generate arbejdsmarked = ibeskaef[1]==5 | studerende[1]==1
bysort respondent (round): generate udearbejdsmarked = udenbeskaef[1]==5 | pensionist[1]==1 | andet[1]==1

** Urbanisering
recode urban (1 2 = 1 "Storby/forstad") (3 = 2 "Mellem by") (4 5 = 3 "Landet"), gen(urban2)

bysort respondent (round): generate urban1 = urban2[1]

** Afstand til supermarked
encode(daglig_1_other), gen(supermarked1)
recode supermarked (1 3 4 = 0) (2 6 15 16 26= 1) (7 27 28 = 2) (8 30 = 3) (9 31 = 4) (10 33 = 5) (11 34 = 50) (12 35 36 = 6) (5 13 37 = 7) (14 39 = 8) (41 = 9) (17 = 10) (18 = 100) (19 = 11) (20 21 = 12) (22 = 13) (23 = 14) (24 = 15) (25 = 18) (29 = 20) (32 = 49) (38 = 73) (40 = 80), gen(supermarked2)

bysort respondent (round): generate supermarked = supermarked2[1]

gen z_supermarked = (supermarked-1.403138)/4.599395

** Exposure, mediator, outcome

** Netværk/Social kapital
foreach v of varlist skfam_1 skfam_2 skfam_3 skfam_4 skfam_5 {
recode `v' (0 1 = 0) (2 = 1) (3 = 2) (4 = 3) (else=.), gen(`v'1)
}

gen netvaerk = skfam_11 + skfam_21 + skfam_31 + skfam_41 + skfam_51

tab netvaerk

sum netvaerk

tab1 skfam_1 - skfam_5


generate forening = 0
replace forening = 1 if skfam_5==4 | skfam_5==3

generate venner = 0 if round==1
replace venner=1 if skfam_2==4 | skfam_2==3

generate familie = 0 if round==1
replace familie=1 if skfam_1==4 | skfam_1==3

tab familie skfam_1

bysort respondent (round): generate familie

xtile netvaerk_4 = netvaerk, nq(4)
tab netvaerk_4


generate netvaerk_bin = netvaerk>=9

** Ny mobilisering
foreach v of varlist hjboern - hjfungere {
recode `v' (2 3 = 1) (1 4 = 0) (else=.), gen(`v'a)
}

gen ikkemob = 0
replace ikkemob = 1 if hjboern2==1 | hjinforma==1 | hjindkoeba==1 | hjtransporta==1 | hjdonationa==1 | hjfungerea==1

tab ikkemob round


** Modtage hjælp
tab1 hjboern
foreach v of varlist hjboern - hjfungere {
recode `v' (1 2 = 1) (3 4 = 0) (else=.), gen(`v'1)
}

foreach v of varlist hjboern - hjfungere {
recode `v' (3 = 1) (1 2 4 = 0) (else=.), gen(`v'2)
}

gen mob_modtage2 = 0
replace mob_modtage2=1 if hjboern2==1 | hjinform2==1 | hjindkoeb2==1 | hjtransport2==1 | hjdonation2==1 | hjfungere2==1

foreach v of varlist hjboern - hjfungere {
recode `v' (1 = 1) (2 3 4 = 0) (else=.), gen(`v'3)
}

gen mob_modtage3 = 0
replace mob_modtage3=1 if hjboern3==1 | hjinform3==1 | hjindkoeb3==1 | hjtransport3==1 | hjdonation3==1 | hjfungere3==1

tab mob_modtage2 round
mob_modtage3

gen mob_modtage1 = 0
replace mob_modtage1=1 if hjboern1==1 | hjinform1==1 | hjindkoeb1==1 | hjtransport1==1 | hjdonation1==1 | hjfungere1==1

bysort respondent (round): gen mob_modtage = mob_modtage1[2]

** Give hjælp
foreach v of varlist frboern_1 - frboern_7 {
recode `v' (1 = 1) (2 3 = 0) (else=.), gen(`v'1)
}

gen mob_give1 = 0
replace mob_give1=1 if frboern_11==1 | frboern_21==1 | frboern_31==1 | frboern_41==1 | frboern_51==1 | frboern_61==1 | frboern_71==1

bysort respondent (round): gen mob_give = mob_give1[2]

** Både modtage og give samlet
gen mob_begge = 0
replace mob_begge=1 if mob_modtage==1 | mob_give==1

** Self-efficacy
tab bekaempe round
tab hjaelpeloes 

bysort respondent (round): gen efficacy = bekaempe[3]
bysort respondent (round): gen minustro = hjaelpeloes[3]

* Fjern missing/Datarens
foreach var in kvinde ung_alder mid_alder gam_alder risiko daarligthelbred grundskolde kvu mvu lvu supermarked {
drop if missing(`var')
}

foreach var in mob_give mob_modtage mob_begge {
drop if missing(`var')
}

drop if missing(efficacy)

** ANALYSE 1: Socioøkonomi --> Netværk
regress netvaerk i.beskaef_h i.udgrp kvinde mid_alder gam_alder z_supermarked

** ANALYSE 2: Netværk --> Mobilisering --> self-efficacy
regress minustro i.koen i.alder_grp i.udgrp i.venner ikkemob venner#i.ikkemob


regress efficacy mob_begge kvinde mid_alder gam_alder i.beskaef_h risiko daarligthelbred

** Kausal meditationsanalyse
paramed minustro, avar(venner) mvar(ikkemob) cvars(kvinde) a0(0) a1(1) m(0) yreg(linear) mreg(logistic) nointeraction 

paramed efficacy, avar(netvaerk_bin) mvar(mob_begge) a0(0) a1(1) m(0) yreg(linear) mreg(logistic)